Used data in this analysis

Specifically, in this experiment set, known experiment labels are:

  • [C] GSM2858678
  • [C] GSM2858686
  • [C] GSM2858688
  • [C] GSM2858692
  • [C] GSM2858694
  • [C] GSM2858699
  • [C] GSM2858701
  • [C] GSM2858705
  • [C] GSM2858713
  • [C] GSM2858726
  • [C] GSM2858727
  • [C] GSM2858739
  • [C] GSM2858742
  • [C] GSM2858746
  • [C] GSM2858748
  • [C] GSM2858749
  • [C] GSM2858761
  • [C] GSM2858766
  • [C] GSM2858767
  • [C] GSM2858780
  • [C] GSM2858792
  • [T] GSM2858682
  • [T] GSM2858690
  • [T] GSM2858707
  • [T] GSM2858711
  • [T] GSM2858716
  • [T] GSM2858718
  • [T] GSM2858729
  • [T] GSM2858760
  • [T] GSM2858772
  • [T] GSM2858789

General description

This report contains all the functional information that was requested by the options when functional_Hunter.R was executed. The functional categories can be:

  • KEGG pathways
  • GO:
    • Biological Process
    • Molecular Function
    • Cellular Component
  • Reactome pathways
  • Custom nomenclature

All the functional categories are computed with CluterProfiler and GO caterogires are computed also with TopGo. Some sections will not show if there are not sinficative results. Each category is analysed using Over representation analysis (ORA) and Gene Set Analysis (GSEA). The ORA method takes a group of significative DEGs (only DEGs, upregulated DEGs or downregulated DEGs) and performs a hypergeometric test for each term of the selected functional category. In the case of the GSEA method, all the genes are sorted by their fold-change and the algorithm scan which genes with similar fold-change shares a term of the selected functional category.

Statistics about input results obtained from DEGenes Expression Hunter are:

Gene_tag Genes
PREVALENT_DEG 22552

Top genes

Table of signifcant genes. Variables taken into account are being shown into table (except gene symbols/ID). Top of positive (0 items) and negative (0 items) are being shown in two different tables

Top positive

Top negative

MF - Over Representation Analysis

The ORA method takes a group of significant genes and performs a Fisher’s exact test for each term of the selected functional category.

Barplot

The most highly signficant categories in ascending order, according to adjusted p-value. The x-axis represents the number of significant genes found within the functional category.

Dotplot

The most highly signficant categories in descending in categories of gene ratio, defined as the proportion of significant genes that are found in the functional category. The x-axis represents the gene ratio and the dot size the number of genes associated with the functional category.

Gene-Concept Network

The network connects the top functional categories (brown nodes) to their associated genes (grey or colored nodes). The size of the functional category nodes shows the number of connected genes.

Cnetplot is not readable because more than 200 genes has been enriched in this nomenclature, so is not printed

Enrich Map plot

The top functional categories (nodes), connected if they share genes. Edge thickness represents the number of shared genes. Nodes size represents the number of significant genes within the category.

Heatplot

Significant genes (x-axis) and the functional categories in which they appear.

Upsetplot

Genes are clustered according to shared enriched categories. The y-axis shows the number of genes belonging to the different clusters (top) and categories to which they belong (bottom).

BP - Over Representation Analysis

The ORA method takes a group of significant genes and performs a Fisher’s exact test for each term of the selected functional category.

Barplot

The most highly signficant categories in ascending order, according to adjusted p-value. The x-axis represents the number of significant genes found within the functional category.

Dotplot

The most highly signficant categories in descending in categories of gene ratio, defined as the proportion of significant genes that are found in the functional category. The x-axis represents the gene ratio and the dot size the number of genes associated with the functional category.

Gene-Concept Network

The network connects the top functional categories (brown nodes) to their associated genes (grey or colored nodes). The size of the functional category nodes shows the number of connected genes.

Cnetplot is not readable because more than 200 genes has been enriched in this nomenclature, so is not printed

Enrich Map plot

The top functional categories (nodes), connected if they share genes. Edge thickness represents the number of shared genes. Nodes size represents the number of significant genes within the category.

Heatplot

Significant genes (x-axis) and the functional categories in which they appear.

Upsetplot

Genes are clustered according to shared enriched categories. The y-axis shows the number of genes belonging to the different clusters (top) and categories to which they belong (bottom).

CC - Over Representation Analysis

The ORA method takes a group of significant genes and performs a Fisher’s exact test for each term of the selected functional category.

Barplot

The most highly signficant categories in ascending order, according to adjusted p-value. The x-axis represents the number of significant genes found within the functional category.

Dotplot

The most highly signficant categories in descending in categories of gene ratio, defined as the proportion of significant genes that are found in the functional category. The x-axis represents the gene ratio and the dot size the number of genes associated with the functional category.

Gene-Concept Network

The network connects the top functional categories (brown nodes) to their associated genes (grey or colored nodes). The size of the functional category nodes shows the number of connected genes.

Cnetplot is not readable because more than 200 genes has been enriched in this nomenclature, so is not printed

Enrich Map plot

The top functional categories (nodes), connected if they share genes. Edge thickness represents the number of shared genes. Nodes size represents the number of significant genes within the category.

Heatplot

Significant genes (x-axis) and the functional categories in which they appear.

Upsetplot

Genes are clustered according to shared enriched categories. The y-axis shows the number of genes belonging to the different clusters (top) and categories to which they belong (bottom).

Values of options passed to the Functional Hunter main function

First column contains the option names; second column contains the given values for each option. Note that large data objects (e.g. expression results, organism table and custom annotation files) are not shown.

final_main_params
model_organism Human
annot_table NULL
input_gene_id ENTREZID
custom NULL
enrich_dbs c(“MF”, “BP”, “CC”)
kegg_data_file
enrich_methods ORA
annotation_source orgdb
pthreshold 0.1
qthreshold 0.2
cores 1
task_size 1
output_files results
fc_colname mean_logFCs
universe NULL
clean_parentals FALSE
simplify FALSE
top_categories 50
sim_thr NULL
summary_common_name ancestor